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Bounds in multi-horizon stochastic programs

  • S.I.: Stochastic Optimization: Theory & Applications in Memory of M.Bertocchi
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Abstract

In this paper, we present bounds for multi-horizon stochastic optimization problems, a class of problems introduced in Kaut et al. (Comput Manag Sci 11:179–193, 2014) relevant in many industry-life applications typically involving strategic and operational decisions on two different time scales. After providing three general mathematical formulations of a multi-horizon stochastic program, we extend the definition of the traditional Expected Value problem and Wait-and-See problem from stochastic programming in a multi-horizon framework. New measures are introduced allowing to quantify the importance of the uncertainty at both strategic and operational levels. Relations among the solution approaches are then determined and chain of inequalities provided. Numerical experiments based on an energy planning application are finally presented.

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Notes

  1. See https://pvwatts.nrel.gov/.

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Authors and Affiliations

  1. Department of Management, Economics and Quantitative Methods, University of Bergamo, Via dei Caniana 2, 24127, Bergamo, Italy

    Francesca Maggioni

  2. Department of Economics and Management, Brescia University, Contrada S. Chiara 50, 25122, Brescia, Italy

    Elisabetta Allevi

  3. Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Høgskoleringen 1, 7491, Trondheim, Norway

    Asgeir Tomasgard

Authors
  1. Francesca Maggioni
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  2. Elisabetta Allevi
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  3. Asgeir Tomasgard
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Correspondence to Francesca Maggioni.

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The idea of this work was originated by a discussion with Marida Bertocchi. The authors would like to express their gratitude for being an exceptional colleague and friend. This work is dedicated to her memory.

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Maggioni, F., Allevi, E. & Tomasgard, A. Bounds in multi-horizon stochastic programs. Ann Oper Res 292, 605–625 (2020). https://doi.org/10.1007/s10479-019-03244-9

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  • DOI: https://doi.org/10.1007/s10479-019-03244-9

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